infrastructures

Article

BIM-Based Description of Intelligent Transportation Systemsfor Roads

Mahsa Mirboland 1,∗ and Kay Smarsly 2

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Citation: Mirboland, M.; Smarsly, K.

BIM-Based Description of Intelligent

Transportation Systems for Roads.

Infrastructures 2021, 6, 51.

https://doi.org/

10.3390/infrastructures6040051

Academic Editor: Isam Shahrour

Received: 2 March 2021

Accepted: 23 March 2021

Published: 26 March 2021

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1 Computing in Civil Engineering, Bauhaus University Weimar, 99423 Weimar, Germany2 Institute of Digital and Autonomous Construction, Hamburg University of Technology, 21079 Hamburg,

Germany; kay.smarsly@tuhh.de* Correspondence: mahsa.mirboland@uni-weimar.de; Tel.: +49-3643-58-4220

Abstract: Intelligent transportation systems (ITS) provide safer, greener, and more convenient mo-bility, while reducing the impact on the environment. In recent years, simulation platforms havebeen employed to study ITS applications, mostly focusing on traffic-related simulations. Despiteseveral research studies on ITS applications and simulation platforms, formal semantic descriptionsof intelligent transportation systems have not been addressed yet. In this paper, a semantic modeldescribing intelligent transportation systems for roads is proposed. The semantic model is devised toprovide a basis for designing ITS simulation platforms. Building upon the semantic model, an exten-sion to an open building information modeling (BIM) standard, i.e., the Industry Foundation Classes(IFC) schema, is presented. The IFC schema extension is verified and validated using a BIM-basedsimulation scenario of ITS for roads. It is shown that the proposed IFC-compliant description of ITSfor roads provides a formal basis for generating BIM-based simulations and hence facilitates ITS in-frastructure modeling in BIM projects. It is concluded that the present work represents a cornerstonefor designing BIM-based ITS simulation platforms. In future endeavors, potential standardizationand formalization efforts may be discussed.

Keywords: intelligent transportation systems; semantic modeling; Building Information Modeling(BIM); Industry Foundation Classes (IFC); vehicular cloud; EXPRESS; STEP

1. Introduction

Constituting key elements of smart cities, intelligent transportation systems offersafer commutes, efficient mobility, and reduced environmental impacts, while increasingconvenience and quality of life. An intelligent transportation system (ITS) is a coupledapplication consisting of several vehicular cyber-physical systems (VCPS). Intelligenttransportation systems represent vehicles as smart components of vehicular cyber-physicalsystems with on-board sensing/actuating, computing, and communication capabilities [1].Intelligent transportation systems are applicable for all modes of transport, e.g., road,aviation, maritime, and railway transport.

Intelligent transportation systems for roads refer to land-based systems that use roadsas travel routes. Traffic management and public transportation control, road safety, andhazard management are among the most important applications of intelligent transporta-tion systems for roads [2]. An ITS for roads comprises different data-sharing processeswith intermittent connections and various applications, entailing a complex, heterogeneoussystem [3,4]. Therefore, it is vital to design simulation platforms for monitoring, evaluating,and optimizing the performance of ITS for roads. ITS simulation platforms essentially inte-grate computational models, aiming to investigate ITS capabilities, design flaws, potentialimprovements, and future mobility demands [5,6].

In the last decade, ITS simulation platforms have been employed to study ITS struc-tures pertinent to specific use cases, e.g., traffic management applications or public trans-portation systems. Boschian et al. (2011) have proposed a reference framework of inter-

Infrastructures 2021, 6, 51. https://doi.org/10.3390/infrastructures6040051 https://www.mdpi.com/journal/infrastructures

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modal transportation systems with an information management layer between differentmodes of transport [7]. The reference framework integrates a simulation module andforms a platform for operational processes. Ghariani et al. (2014) have presented a com-parative analysis framework for performance assessment of existing simulation platformsused for public transport control systems [8]. A model-driven engineering frameworkfor implementing ITS simulations for roads has been proposed in [9]. The frameworkcomprises ITS data models for traffic simulations and sensor network components, as wellas guidelines on how to use the data models for different simulations, such as traffic lightscontrol. Datta et al. (2016) have presented a semantics-based framework addressing ITSbuilding blocks and different operational phases of ITS software elements, obtained todescribe interconnected vehicles in the Internet of Things (IoT) ecosystem [10].

Research on ITS simulation platforms has mostly focused on improving simulationsof traffic-related applications [11,12]. Although BIM for infrastructure is a matter of recentresearch [13–16], formal descriptions of ITS for roads that provide a basis for simulationplatform designs have received little attention [17]. Standardized formal descriptions, e.g.,based on open building information modeling (OpenBIM), may be used for describinginfrastructure information for physical components in ITS for roads. OpenBIM data models,i.e., the Industry Foundation Classes (IFC) schema maintained by buildingSMART Interna-tional (bSI), provide neutral non-proprietary data models for collaborative descriptions ofinfrastructure in the architecture, engineering, and construction (AEC) industry [18].

The current official IFC schema, standardized in ISO 16739-1:2018, includes severalIFC entities that may be used to describe road infrastructure, such as the IfcAlignmententity, which defines reference systems for locating infrastructure elements [19]. Further-more, within collaborative projects, researchers and organizations have been developingextensions to IFC entities that may be obtained to define physical and spatial elementsof road infrastructure, with the potential of becoming candidate entities of official IFCschemas [20–22]. The IFC Road project, conducted by bSI, aimed to create a candidate stan-dard, which extends the IFC schema for roads, e.g., developing data models for geometry,road body shape, earthwork, and semantic information for roads, and integrating use casesrelevant to the road life cycle. With all deliverables of the IFC Road being published, theproject was finalized in 2020 [23].

Moreover, several studies have been conducted to integrate further infrastructureelements into the IFC schema. For example, Lee and Kim (2011) have proposed an IFCextension for road structure, defining infrastructure segments in terms of IFC entities,such as IfcPavementLayer, IfcBridgePier, IfcTunnelLining, and IfcInspectionLadder [24]. Theauthors have used an example of a road section with combined bridge and tunnel segmentsto validate the proposed IFC extension, illustrating entities that define longitudinal andcurvilinear sections of road infrastructure. Amann et al. (2015) have shown the extendibilityof IFC Alignment when introducing the IfcCrossSections entity, which defines static anddynamic cross sections for junction-free roads [25]. A comparative study between theIFC schema and spatial elements required for tunnel design is presented in [26]. Theauthors later introduced an extension that defines entities for main components in tunnelstructures, such as IfcShotcrete, IfcSteelRib, IfcRockBolt, and IfcConcreteLining, and havevalidated the extension using a real tunnel construction, which has been compared with anIFC-based BIM model. Park et al. (2018) have defined additional elements for semanticinformation management of steel box girder bridges using Industry Foundation Classes,Version 4 (IFC4), with user-defined property sets for spatial arrangement of the structureand physical structural components during planning and design phases [27].

Despite the extensive capabilities to describe infrastructure information for physi-cal road components, the IFC schema provides just a few entities that may be used fordescribing the “cyber” components of ITS for roads. For example, IfcSensor provides asensor description for predefined objects, such as temperature sensors, and may partiallybe employed to define sensing units of ITS intelligent infrastructure. The IFC entity IfcCom-municationsApplicance may specify communication units of ITS intelligent infrastructure

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using predefined property sets [28]. Although not specifically designed for describing ITS,studies have been conducted aiming to fill the gap in data models for cyber-physical compo-nents, such as actuators and sensor networks. Smarsly et al. (2017) have presented an IFCextension that defines entities related to cyber-physical systems deployed for monitoringand control applications [29]. The authors have defined IfcSensorNode, IfcSensorNetwork,and IfcMonitoringControlSystem as CPS-related new IFC entities to describe sensor nodes,sensor networks, and structural health monitoring (SHM) and control systems, respectively.Later, Theiler and Smarsly (2018) defined IFC Monitor, an IFC extension for describingmonitoring-related information, adding enumeration entities IfcNetworkTopologyEnum andIfcSensorTypeEnum for predefined network topologies and additional sensor types, respec-tively [30].

From the information stated above, it is concluded that the existing capabilities ofthe IFC schema for describing intelligent transportation systems are limited to a few IFCentities for describing infrastructure information for physical road components. To this end,an extension to the IFC schema is required to fill the gap with respect to entities devisedfor describing the “cyber” components of ITS for roads, i.e., entities not yet available inthe IFC schema but relevant to BIM-based modeling of ITS for roads. In this paper, forcreating a formal description of ITS for roads facilitating BIM-based simulations, a semanticmodel for ITS for roads is proposed. The remainder of the paper is structured as follows:In Section 2, sources that provide knowledge relevant to semantic descriptions of ITS forroads are analyzed. Section 3 presents the semantic model and an illustrative exampledevised to validate and verify the proposed model. Then, in Section 4, an IFC schemaextension is presented and validated to map the semantic model into BIM data models.Section 5 summarizes the present work and concludes with an outlook on potential futurework.

2. Knowledge Sources for Semantic Modeling of ITS

Defining a formal basis for ITS simulation platforms requires full consideration ofphysical, computing, and networking subsystems of intelligent transportation systems. Inthis section, focusing on road transport, ITS components and relationships between com-ponents, as well as standards and protocols that ensure sound ITS operations (hereinaftertermed “knowledge sources”), are categorized and analyzed to be adequately reflected inthe semantic model. The knowledge sources are divided into four categories, ITS architec-ture, applications, intelligent infrastructure, and communications, which are illuminatedin the following subsections. Figure 1 shows a taxonomy of the knowledge sources alongwith respective concepts and terms relevant to each knowledge source.

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Figure 1. Taxonomy of the knowledge sources relevant to this study.

2.1. ITS Architecture

Vehicular ad-hoc networks are the central paradigm relevant to ITS architectures. Avehicular ad-hoc network (VANET) is a self-forming network based on wireless vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. Nodes of a VANETcomprise vehicles and infrastructure equipped with networking devices, connected throughVANET communications [31]. The architecture of vehicular ad-hoc networks may becategorized into pure cellular or wireless local area networks, pure ad hoc networks,and hybrid networks [32]. However, intermittent and autonomous connections betweennetwork nodes may cause frequent changes in VANET topologies. Varying traffic densities,heterogeneous vehicle paths in urban areas, and limited wireless transmission ranges andchannel bandwidths pose challenges to VANET communications [33]. Thus, differentrouting protocols and security standards are employed for vehicular ad-hoc networks toguarantee sound data packet transmissions and secure communications [34].

Combining the VANET paradigm with the IoT in vehicular environments, i.e., theInternet of Vehicles, has led to the vehicular cloud concept, an efficient ecosystem forITS networks [35]. The term “autonomous vehicular cloud” has been coined to denotea group of autonomous vehicles that share on-board resources and services with otherauthorized network nodes using vehicle-to-anything (V2X) communications. Therefore,by renting under-utilized vehicle resources and decentralizing data processing, vehicularclouds broaden ITS applications to non-safety location-specific applications [36].

Vehicular cloud computing and information-centric networking are the key attributesof vehicular clouds, facilitating robust resource-sharing processes. The automotive industrycontinuously produces vehicles with powerful on-board resources, enabling vehicles tosense and to store data from the environment, to process the data, and to react appro-priately to the data. Thus, vehicles, recording data that are locally relevant, are enabledto efficiently manage time-sensitive operations. However, the potential of computingand communication capabilities of vehicles has not been fully exploited [37]. Vehicularcloud computing (VCC) is a mechanism that combines underutilized vehicular cyber-physical system resources to perform ITS applications. In other words, VCC eliminates

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the need for centralized data-processing infrastructure by distributing the computingload on network nodes [38]. Information-centric networking (ICN) is a data-networkingparadigm that puts emphasis on the content of data packets by decoupling the packetsfrom node addresses [39]. Several ICN architectures and messaging protocols exist thatspecify standardized, machine-readable naming and beacon exchange between networknodes [40,41].

An example of vehicular cloud formation is shown in Figure 2, where V2X andinfrastructure-to-infrastructure (I2I) communications facilitate data packet transmissionsbetween network nodes in the corresponding vehicular clouds. Using VCC under normalconditions on the road, vehicles driving in the same direction may form vehicular clouds toprocess computing tasks, disseminate the information to neighboring nodes, or store andlater share data packets to ITS users. ICN is of specific importance in hazardous situations,e.g., in case of accidents, where vehicles approaching a hazardous section and/or roadfurniture, such as traffic cameras, form intermittent vehicular clouds, disseminating alertmessages and notifying traffic to avoid congestion, chain accidents, and probable casualties.

Figure 2. Vehicular cloud formations in ITS for roads.

Built upon VANET and taking advantage of VCC and ICN, vehicular clouds constituteboth static clouds (e.g., in parking lots) and dynamic clouds (en route applications), hencecovering a wide range of applications of ITS for roads. Consequently, in this study, vehicularclouds are considered the basic network architecture to be reflected in the semantic model.

2.2. ITS Applications

Different implementation strategies and design requirements have led to a plethora ofITS applications, the second category of knowledge sources relevant to the semantic model.Designing frameworks that focus on traffic information generation and urban mobility de-mands has been frequently addressed in the past decade [42,43]. Therefore, ITS applicationsare often solely regarded as traffic-related applications, such as traffic lights monitoringsystems and public transportation control systems [44]. However, with the advent ofvehicular clouds, cloud-based services and applications have been introduced [45].

As for the variety of existing applications, many application categories have beenproposed with respect to different aspects of ITS architecture. For example, regarding ITScommunication networks, the European Telecommunications Standards Institute (ETSI)groups ITS applications into the categories cooperative traffic efficiency, active road safety,cooperative local services, and global Internet services [46]. Cooperative traffic efficiencyaims at improving the traffic flow and is further categorized into speed managementand cooperative navigation applications. Active road safety comprises driving assistanceapplications and warning scenarios, aiming to increase cooperative awareness to preventhazardous situations. Cooperative local services include applications for location-basedservices, such as point-of-interest notifications and media downloading. Last, but notleast, global Internet services comprise applications for community services and life-

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cycle management of ITS infrastructure, such as insurance and financial services andinfrastructure software provisioning and update. In this study, a categorization of ITSapplications is defined as follows:

• Traffic management, granting optimized commutes and efficient mobility by reducingtravel duration and fuel consumption, offers alternative routes in case of emergencyand traffic flow control. Urban mobility controls, such as traffic lights control systemsand public transportation control systems, are also included in this category.

• Maintenance management comprises continuous monitoring and assessment of intelli-gent road infrastructure and road conditions using real-time data exchange. In-timealerting for detours in case of disasters or accidents, road services such as winter roadmaintenance, and structural damage detection and reconstruction process manage-ment are typical examples of applications in this category.

• Telematics, combining telecommunications and informatics, represent on-board ap-plications that monitor the performance of vehicle on-board functional processes(“intra-vehicle monitoring”) and provide driving assistance services. Autonomousdriving is one of the most important applications in this category.

• Infotainment, merging information and entertainment, offers Internet-based services(such as online media platforms and on-demand information) to passengers forincreasing the en route comfort.

While emphasis is put on traffic management and maintenance management scenarios,the semantic model presented in this study must be able to describe all the above-mentionedapplication categories. Traffic efficiency and safety messages are prioritized to be includedin the ITS semantics for roads. In the following subsection, ITS intelligent infrastructure,representing a crucial element when implementing ITS applications, is discussed.

2.3. ITS Intelligent Infrastructure

The facilities underlying road intelligent transportation systems enable sensing ofthe vehicular environment, supporting physical and computational processes, and con-trolling ITS applications. Therefore, it is vital to determine ITS infrastructure capabilitiesand resources to be reflected in the semantic model. ITS infrastructure is composed of(i) physical and spatial structural elements, i.e., road infrastructure, as well as (ii) a set offunctional elements that together build the ITS architecture, the latter hereinafter termed“ITS stations”.

Regarding road intelligent transportation systems, ITS stations, whether fixed ormobile, are the core elements that add intelligence to roads. ITS stations, according to [47],may further be categorized into the following:

• Vehicle ITS stations (mobile), i.e., vehicular cyber-physical systems that comprise allvehicle types in vehicular environments, e.g., cars, trucks, and motorbikes;

• Roadside ITS stations (fixed) that represent traffic shields and cameras, poles, andgantries;

• Personal ITS stations (mobile), i.e., smart devices, such as cellphones and tablets; and• Central ITS stations (fixed), also known as “control centers”.

Different technologies enable ITS stations to interact with the vehicular environment.Regardless of underlying technologies, ITS stations are equipped with four main on-boardresources, (i) sensing unit, (ii) computing unit, (iii) communication unit, and (iv) power unit.The sensing unit implements sensor networks and technologies, such as traffic detectionsystems and environmental-changes detectors. Micro-electro-mechanical systems (MEMS),inductive loops, radio-frequency identification (RFID), light detection and ranging (LiDAR)sensors, and automatic license plate recognition cameras are widely used components oftraffic detection systems. Wheel speed sensors, rear object laser radars, and blind spotdetection sensors are part of on-board sensing units in vehicle ITS stations. The mainprocessing board and storage device that controls the computational processes constitutethe computing unit. Communication devices, e.g., beacons, transceivers and routers, are

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represented by the communication unit, while the power unit comprises power-supplymeans, e.g., photovoltaic panels, piezoelectric transducers, or the electrical grid. In additionto the four main units, dedicated ITS stations may include actuating and control devices tocomply with traffic and safety demands, to prevent hazardous situations, or to change thebehavior of ITS stations.

Summarizing the information stated above, ITS stations are decent candidates fordescribing ITS intelligent infrastructure on a technology-independent semantic basis. There-fore, in this paper, ITS intelligent infrastructure is reflected in the semantic model in termsof vehicle, roadside, personal, and central ITS stations with on-board sensing, computing,communication, and power units. In the following subsection, connections between ITSstation on-board resources, as well as communications between ITS stations that facilitatedata sharing process, are shown.

2.4. ITS Communications

on-board communication capabilities allow ITS intelligent infrastructure to cooper-atively connect to network nodes and to share resources without the need for a middle-ware or coordinating infrastructure, entailing cooperative ITS (C-ITS) communication [48].Wireless communication is the cornerstone of C-ITS communication and is leveraged byscalability and easy deployment in vehicular environments. The ETSI TR 101 607 technicalreport lists standards, protocols, and specifications applied to C-ITS communications inEurope with respect to traffic efficiency and road safety requirements [49]. The architectureof ITS communication networks, to be reflected in the semantic model, is illustrated inFigure 3. Based on [50], ITS communication networks are in general categorized intoITS station internal networks and ITS station external networks; the latter include an ITSdomain and a generic domain, as will be illuminated in the following paragraphs.

Figure 3. ITS communication networks.

An ITS station internal network denotes communications within one ITS station. ITSstation internal networks are defined in terms of a reference architecture based on layeredcommunication protocols consisting of applications, facilities, networking and transport,access, management, and security layers. Each layer characterizes different functionalitiesand protocols relevant to ITS stations. For example, the ITS-G5 protocol characterizes accesslayer specifications for dedicated short-range communications in the 5.9 GHz frequencyband [51], and GeoNetworking is a family of networking protocols that transports datapackets based on geographical positions of the network nodes [50]. Every ITS stationinternal network possesses physical on-board equipment and devices, such as sensors,

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transceivers, and mechanical and/or electrical actuators, which are characterized andpresented by the proprietary network. Only an ITS station internal network can access theproprietary network of the same ITS station.

ITS station external networks are composed of a generic domain and an ITS domain.The generic domain includes an access network to provide information to ITS users publicly,i.e., through public access networks, an access point to provide authorized closed groupsof users with specific data, i.e., through private access networks, and a core network thatprovides access to the Internet, i.e., through core networks. In the ITS domain, the ITSad-hoc network ensures wireless C-ITS communication between ITS stations, and the ITSaccess network provides direct connections between ITS station internal networks and thegeneric domain in ITS station external networks.

ITS station external networks exploit ITS station internal networks for combiningon-board under-utilized resources of ITS stations, for transmitting data, and eventuallyfor performing ITS applications. Therefore, ITS station external and internal networks,representing key components of ITS communications, are of notable importance for un-derstanding ITS operations. As a result, direct implications for ITS communications arereflected by introducing ITS station external and internal networks in the semantic model.

3. A Semantic Model for Intelligent Transportation Systems

In this section, the semantic model for intelligent transportation systems for roads ispresented, allowing technology-independent descriptions of road intelligent transporta-tion systems. For validation, the proposed semantic model is instantiated using a cloudformation scenario, illustrating the capabilities of the proposed model to describe ITS forroads on a conceptual level.

3.1. Semantic Content and Structure

The semantic model, representing a metamodel for conceptually modeling ITS forroads, is developed based on the knowledge sources analyzed in the previous section.Figure 4 shows the ITS semantic model in terms of a class diagram. The main elements ofthe semantic model are described in the following paragraphs.

As depicted in Figure 4, the DigitalRoad class represents “non-conventional” roads thatare furnished with ITS intelligent infrastructure. The DigitalRoad class is thus composed ofthe RoadStructure and ITSStation classes. The RoadStructure class displays the underlyingphysical body of a road, including spatial structural elements (e.g., bridges, tunnels, roads,ramps, and resting areas), as well as detailing of structural elements, such as cross sectiongeometry, location, and material properties. Attributes defined for the RoadStructure classmay specify standalone structural elements (e.g., a bridge slab) or grouped structuralelements (e.g., a bridge) using id, geometry, location, and type.

The abstract class ITSStation represents core elements of the ITS architecture. EveryITS station is uniquely defined by an identification number, denoted by the id attribute,and on-board resources, expressed by the resourceUnit attribute. As mentioned earlier,ITS stations may be mobile or fixed. Thus, the ITSStation abstract class is modeled asa superclass of the Mobile and Fixed abstract subclasses. In the abstract class ITSStation,the attribute isFixed, with an initial value of false, represents mobile ITS stations. TheMobile abstract subclass is further categorized into Personal and Vehicle subclasses, whichrepresent personal smart devices and vehicles of any type, respectively. The Fixed abstractsubclass is depicted as a parent class to Central and Roadside subclasses to account forITS control centers and roadside intelligent infrastructure, respectively. Furthermore, asa specific type of network nodes (Interface NetworkNode), ITS stations may perform avariety of operations, such as data processing, signaling, recording, data packet routing,and resource renting. Moreover, the abstract class ITSStation can perform operations,i.e., measureSpeed(), sendMessage(), receiveMessage(), rentResource(), and checkStatus(). TheSensingUnit, ComputingUnit, PowerUnit, and CommunicationUnit classes, conforming tothe assumptions made in Section 2.3, represent the four main on-board units of all ITS

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stations in the ITS architecture. Therefore, the ITSStation abstract class is connected toSensingUnit, ComputingUnit, PowerUnit, and CommunicationUnit classes using compositionassociations. However, some ITS stations may also have actuating capabilities, suchas roadwork warning devices or traffic signal controllers. The actuating capability isrepresented via the ActuatingUnit class, which is connected to the ITSStation abstract classwith an aggregation relationship.

Figure 4. The semantic model for ITS for roads.

The abstract class ITSCommunication portrays communication in the ITS architecture.The attribute domain represents communications in the generic domain or in the ITS domain,as described above. The communicationType and networkType attributes further character-ize the instances of ITSCommunication abstract class with respect to communication type(internal and external) and network type (ad-hoc, ITS access, public, or private). The Exter-nalNetwork class depicts communications between ITS stations, whereas the InternalNetworkclass presents communications within an ITS station. As introduced earlier, internal net-works are dependent on a reference architecture, which is reflected in the semantic modelas an interface that is realized by the InternalNetwork class. on-board units and all equip-ment and assets attached to each ITS station, whether connected wirelessly or with wires,are denoted by the ProprietaryNetwork class. Based on cooperative ITS communicationsin the vehicular environment, the ExternalNetwork class is categorized into V2X and I2Icommunications. The Wireless abstract class depicts wireless communication technologiesand standards that are specifically deployed and used in the ITS architecture. The chan-nelAllocated attribute lists frequency bands corresponding to different channels allocated tospecific ITS applications. Furthermore, the LongRange and ShortRange subclasses representwireless communication standards and protocols deployed for far-field and near-fieldwireless communications, respectively.

The semantic model illustrated in Figure 4 is designed as a metamodel to describeany instances of intelligent transportation systems with respect to different applications.In the following subsection, for validating the proposed semantic model, an instance, i.e.,a model, of an ITS architecture and a cloud formation in connected vehicle ecosystems isshowcased.

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3.2. Validation of the Semantic Model

To illustrate the relationships between the ITSCommunication, ITSStation, and Road-Structure classes, and for validating the semantic model proposed in the previous sub-section, a benchmark ITS scenario, shown in Figure 5, is semantically modeled. In otherwords, an instantiation of the semantic model as a metamodel is made to describe the ITSscenario, which is instantiated as a model. In the ITS scenario, it is assumed that an accident,e.g., a rear-end collision, occurs in a section of a highway and external networks of ITSstations form a vehicular cloud to disseminate safety-related messages. Therefore, to avoidchain accidents and traffic congestion, and to divert the traffic, ITS stations receive andsend data packets by geographically addressing other nodes with potential interest in thecontent of data packets, or forward data packets to destination nodes.

Figure 5. Cloud formation scenario for validating the proposed semantic model.

In Figure 5, a highway section of the German Autobahn A9, labeled HA9, is shown,where the vehicle ITS station V1 broadcasts collision risk messages using the GeoNetwork-ing protocol (“GeoBroadcast”) to ITS stations in the vicinity with potential interest, e.g.,vehicles approaching towards the accident. The vehicle ITS station V1 uses short-rangewireless communication to send a message (M1) to the vehicle ITS station V2. For sendingand receiving the messages, the vehicle ITS stations V1 and V2 employ the ITS-G5 protocol.V1 also sends a media footage it has recorded from the accident to the nearest infrastructurenode, here roadside ITS station RSU1, using short-range wireless communications (M2). Inturn, vehicle ITS station V2 utilizes the point-to-multipoint networking protocol to ask thenearest infrastructure node (roadside ITS station RSU2) for an alternative route (M3). Usinglong-range wireless communication based on 5G cellular networks and the GeoNetworkingprotocol (“GeoUnicast”), RSU1 requests traffic-related data from the next fixed ITS station,here RSU2, and sends a detouring alert as well as traffic signals to RSU2 (M4).

The scenario shown in Figure 5 is semantically illustrated in Figure 6 in terms ofan object diagram, i.e., an instance of the proposed semantic model. The object diagramcomprises the HA9 object of type RoadStructure, four objects of type Vehicle and Roadside(V1, V2, RSU1, and RSU2), objects of type ITSCommunication characterized by the messagesshared among the ITS stations (M1. . . M4), and Wireless-type objects displaying the wirelesscommunication standards employed for each communication (5G and ITS-G5).

The scenario illustrated above may be interpreted from the object diagram depictedin Figure 6, corroborating that the proposed semantic model may define any scenario ofvehicular cloud formations and ITS for roads, respectively. In the following section, aBIM-based description of ITS for roads in terms of an IFC schema extension is presented.

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Figure 6. Object diagram corresponding to the scenario shown in Figure 5.

4. BIM-Based Description of ITS for Roads

In this section, the IFC schema extension is proposed to describe intelligent transporta-tion systems for roads based on building information modeling. The official IFC schema,in association with IfcRoad introduced above, is used as the baseline schema, upon whichthe IFC schema extension is defined. By mapping the semantic model introduced in theprevious section into the (baseline) IFC schema, the IFC schema extension for ITS for roadsis achieved. In the following, components of the IFC schema extension are explained andverified. The section concludes with a validation procedure conducted on the proposedIFC schema extension.

4.1. An IFC Schema Extension for ITS for Roads

Figure 7 shows the proposed IFC schema extension. The entities, property sets, andan enumeration data type, which are newly proposed in this study (as described below),are shaded in gray.

The IFC schema follows an object-oriented approach based on the EXPRESS datamodeling language, which is standardized in [52]. The IFC schema contains a hierarchy ofseveral layers, in which IFC classes, i.e., IFC entities, are structured from the most abstractentities in the core layer to extensive, domain-specific, and resource-specific entities inupper layers. As can be seen from Figure 7, the entity IfcRoot of the core layer represents themost abstract class relevant to all entity definitions. The IfcRoot entity provides capabilitiesfor globally identifying entities, attributing name and description of entities, and definingownership information of entities. The entities IfcObjectDefinition, IfcPropertyDefinition, andIfcRelationship are subclasses of the IfcRoot entity, representing type and occurrences ofobjects, generalized characteristics assigned to objects, and objectified relationships in theIFC schema, respectively [53].

The IfcObject entity, a subclass of the IfcObjectDefinition entity, defines semantic occur-rences of any “thing” or process. Several subclasses of the IfcObject entity exist, such as theIfcProduct entity, which represents geometrical and spatial objects, and the IfcGroup entity,defining a logical collection of objects. The IfcElement and IfcSpatialElement entities are twosubclasses of the IfcProduct entity. The IfcElement entity defines physical components in an

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AEC product, whereas the IfcSpatialElement entity defines a generalized representation ofcomponents that construct spatial elements for structures. The IfcSpatialStructureElementrepresents spatial elements that construct a unit of project structure, such as constructionsites, spaces, and facilities. The IfcFacility entity further classifies instances of the IfcSpatial-StructureElement entity as built facilities, such as buildings (IfcBuilding), bridges (IfcBridge),and roads (IfcRoad). The IfcRoad entity, representing land routes, is a built facility definedfor highways, streets, cycle, and foot paths. It is worth noting that IfcFacility and IfcRoadentities are included in the latest draft of the IFC schema, but are not yet standardized [54].

Figure 7. Extract of the IFC schema extension showing entities relevant to ITS in gray color.

For describing ITS infrastructure, the IfcITSStation entity is newly defined in thisstudy. The IfcITSStation entity is introduced as a subclass to the IfcDistributionElement entity,which represents elements participating in distribution systems. Additional to attributesinherited, the IfcITSStation entity is specified with attributes StationID of type IfcInteger,HasActuator of type IfcBoolean, and StationType of the IfcITSStationTypeEnum enumerationtype. ITS station types are listed in the enumeration type IfcITSStationTypeEnum as thefollowing constants: VEHICLEUNIT, PERSONALUNIT, ROADSIDEUNIT, CENTRALUNIT,USERDEFINED, and NOTDEFINED. on-board resources of ITS stations are specified usingthe property set Pset_ITSSResources, as shown in Table 1.

The entity IfcSystem presents organized combinations of objects that provide specificservices. As a subclass of the IfcSystem entity, the IfcDistributionSystem entity accounts fornetworks, through which a distribution medium is controlled or maintained. Therefore,intelligent transportation systems may be regarded as distribution systems maintaining ITScommunications and data transmissions among ITS stations. Hence, the IfcRoadITS entityis introduced as a subclass of the IfcDistributionSystem entity for describing instances ofintelligent transportation systems for roads. The IFC schema defines different distributionsystem types using the enumeration type IfcDistributionSystemEnum, listing enumeratorssuch as SIGNAL, DATA, and COMMUNICATION. For describing communications in theITS domain, IfcDistributionSystemEnum of type COMMUNICATION is further specified

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using the property set Pset_DistributionSystemTypeITSC introduced in Table 2. As ITScommunications are a variation of communications in cyber-physical systems, recom-mendations from [55] have been taken into consideration for developing the property setPset_DistributionSystemTypeITSC.

Table 1. Property set Pset_ITSSResources for describing IfcITSStation entities.

Name Type Description

SensingResource P_LISTVALUE/IfcLabel A list of all sensors attached to ITS stations, e.g., MEMS,LiDAR sensors, RFIDs, cameras, and temperature sensors

ComputingResource P_SINGLEVALUE/IfcLabel Description and specification of the on-board computing unitPowerResource P_SINGLEVALUE/IfcLabel Description and specification of the on-board power unitCommunicationResource P_LISTVALUE/IfcLabel Description and specification of the on-board computing unit

and network technologyActuatingResource P_LISTVALUE/IfcLabel A list of all actuating units, if existing, attached to ITS stations,

such as dampers and automatic crossing barriers

Table 2. Property set Pset_DistributionSystemTypeITSC for describing IfcDistributionSystem entities of type COMMUNICA-TION.

Name Type Description

CommunicationType P_ENUMERATEDVALUE/IfcLabel Property enumerators are V2V, V2I,and I2I communication types

CommunicationChannel P_BOUNDEDVALUE/ IfcReal ITS-G5 transmission channel specificationsbased on ETSI EN 302 663 Standard [51]

CommunicationDuration P_LISTVALUE/ IfcTimeMeasure Duration of specific communication sessions

The objectified relationship IfcRelAssignsToGroup assigns object definitions to a group.Here, instances of the IfcITSStation entity (RelatedObjects) are assigned to instances of theIfcRoadITS entity (RelatingGroup). Last, but not least, for connecting the IfcRoad entity as aspatial element to the IfcRoadITS entity, the objectified relationship IfcRelServicesBuildings isused. Listing 1 shows an extract of the extended IFC schema with entities relevant to ITSfor roads denoted in EXPRESS.

Listing 1: Extract of the IFC schema extension in EXPRESS format showing entities relevantto ITS for roads.

...TYPE IfcITSStationTypeEnum = ENUMERATION OF

(VEHICLEUNIT , PERSONALUNIT , ROADSIDEUNIT ,CENTRALUNIT ,USERDEFINED , NOTDEFINED);

END_TYPE;

ENTITY IfcITSStationSUBTYPE OF (IfcDistributionElement);StationID : IfcInteger;HasActuator : IfcBoolean;StationType : IfcITSStationEnum;

END_ENTITY;

ENTITY IfcRoadITSSUBTYPE OF (IfcDistributionSystem);

END_ENTITY;...

The IFC schema extension is verified with respect to syntactic, semantics, and unitcheck criteria using the test software of the official IFC certification program [56,57]. The

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test software verifies the IFC schema extension according to EXPRESS syntax specifications,such as compliance to notational conventions, declarations of entities and data types, anddeclarations of entity attributes and functions. Moreover, since the syntactic criteria are met,the test software is able to generate Java classes for newly defined entities and enumerationdata types. In this study, the test software confirms that no domain rules are violatedand that the proposed IFC schema extension has successfully passed the verification test.Therefore, the proposed IFC schema extension can be used to create BIM-based models ofITS for roads in compliance with IFC syntax and semantics.

4.2. Validation of the IFC Schema Extension

In this subsection, to validate the IFC schema extension, the ITS scenario presented inFigure 5 is described in compliance with the IFC schema. Using the test software introducedabove, the validation process is devised for checking whether the IFC schema extensionprecisely models BIM-based simulations of ITS for roads. For this purpose, the IFC modelthat corresponds to the ITS scenario shown in Figure 5 is created as an instance of the IFCschema extension, using the newly-defined entities, property sets, and the enumerationdata type. The standard for the exchange of product model data (STEP) defines a dataformat for the IFC model [58]. Listing 2, as described below, shows an extract of theSTEP-based IFC model used for the validation process. For greater clarity and transparency,obligatory attributes, such as the global identifiers, are removed from the IFC model shownin Listing 2.

The IFC model shown in Listing 2 includes object entities of type IfcRoad (#1), IfcRoa-dITS (#2), and IfcITSStation (#3 to #6). Attributes of IfcITSStation object entities, such asITS station name, ID, actuating unit (T for true, F for false, i.e., not existing), and type arespecified for each object. Property entities, property set entities, and relationship entities,which assign property set entities to object entities, are exemplarily shown in Listing 2 foronly two ITS stations (#13 to #25). Using IfcPropertySingleValue and IfcPropertyListValueproperty entities, ITS station on-board units for object entities V2 (#13 to #16) and RSU1(#19 to #23) are specified. The IfcPropertySet entity binds property entities in separate sets oftype Pset_ITSSResources and creates V2_Units (#17) and RSU1_Units (#24) property sets forITS stations V2 and RSU1, respectively. Finally, the IfcRelDefinesByProperties relationshipentity is used to link each property set to the respective object entities (#18 and #25). Last,but not least, relationship entities (#33 to #37) define links between object entities (#1 to#6). The IfcRelAssignsToGroup relationship entity is used to specify links between objectentities of type IfcITSStation and IfcRoadITS. For example, the ITS station V1 object ( #3)is integrated in the ITS network and linked to the HA9_TestField object (#2) using theIfcRelAssignsToGroup relationship entity (#33), representing ITS communication betweentwo objects. The IfcRelServicesBuildings relationship entity denotes the link between objectentities of type IfcITSRoad and IfcRoad. Figure 8 shows a visual representation of the IFCmodel of the ITS scenario.

Similar to the steps described above, the STEP-based IFC model is verified using thetest software, which runs syntactic and semantic checks on the IFC model based on the IFCschema extension previously verified. The test software investigates the IFC model againstsyntactic and semantic requirements specified by the official IFC certification program.Several criteria, such as formal compliance with the STEP conventions and the conformanceof data with the IFC schema extension are examined. It can be concluded from the resultsthat the proposed IFC schema extension is capable of describing intelligent transportationsystems in terms of IFC models. The IFC models represent correct information of scenariosin intelligent transportation systems for roads, providing a robust formal basis for designingsimulation platforms and defining various ITS applications.

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Listing 2: Extract of the STEP-based IFC model of the ITS simulation scenario.

...\#1= IFCROAD (\$,\$,’HA9 ’,\$,\$,\$,\$,\$,\$);\#2= IFCROADITS (\$,\$,’HA9_TestField ’,\$,\$,\$,\$);\#3= IFCITSSTATION (\$,\$,’V1 ’,\$,\$,\$,\$,\$,935,.F.,. VEHICLEUNIT .);\#4= IFCITSSTATION (\$,\$,’V2 ’,\$,\$,\$,\$,\$,913,.F.,. VEHICLEUNIT .);\#5= IFCITSSTATION (\$,\$,’RSU1 ’,\$,\$,\$,\$,\$,42,.F.,. ROADSIDEUNIT .)

;\#6= IFCITSSTATION (\$,\$,’RSU2 ’,\$,\$,\$,\$,\$,40,.T.,. ROADSIDEUNIT .)

;...\#13= IFCPROPERTYLISTVALUE(’SensingResource ’,\$,( IFCLABEL(’GPS ’),

IFCLABEL(’RADAR ’),IFCLABEL(’Front CCD ’)) ,\$);\#14= IFCPROPERTYSINGLEVALUE(’ComputingResource ’,\$,IFCLABEL(’EvoTRAC

-G103 ’) ,\$);\#15= IFCPROPERTYSINGLEVALUE(’PowerResource ’,\$,IFCLABEL(’On-board

Power ’) ,\$);\#16= IFCPROPERTYLISTVALUE(’CommunicationResource ’,\$,

(IFCLABEL(’Short -range WiFi ’),IFCLABEL(’Bluetooth 5’)) ,\$);\#17= IFCPROPERTYSET (\$,\$,’Pset_ITSSResources ’,’V2_Units

’ ,(\#13 ,\#14 ,\#15 ,\#16));\#18= IFCRELDEFINESBYPROPERTIES (\$,\$,\$,\$ ,(\#4) ,\#17);\#19= IFCPROPERTYLISTVALUE(’SensingResource ’,\$,( IFCLABEL(’LiDAR ’),

IFCLABEL(’Wind ’),IFCLABEL(’Daylight ’),IFCLABEL(’Temperature ’)) ,\$);

\#20= IFCPROPERTYSINGLEVALUE(’ComputingResource ’,\$,IFCLABEL(’UNO-2271G’) ,\$);

\#21= IFCPROPERTYSINGLEVALUE(’PowerResource ’,\$,IFCLABEL(’ElectricGrid ’) ,\$);

\#22= IFCPROPERTYLISTVALUE(’CommunicationResource ’,\$,(IFCLABEL(’Long -range WiFi ’),IFCLABEL(’Internet Gateway ’)),\$);

\#23= IFCPROPERTYLISTVALUE(’ActuatingResource ’,\$,(IFCLABEL(’Announcement board ’),IFCLABEL(’Solar cell switch ’)),\

$);\#24= IFCPROPERTYSET (\$,\$,’Pset_ITSSResources ’,’RSU1_Units ’,

(\#19 ,\#20 ,\#21 ,\#22 ,\#23));\#25= IFCRELDEFINESBYPROPERTIES (\$,\$,\$,\$ ,(\#5) ,\#24);...\#33= IFCRELASSIGNSTOGROUP (\$,\$,’M1 ’,\$ ,(\#3) ,.PRODUCT . ,\#2);\#34= IFCRELASSIGNSTOGROUP (\$,\$,’M2 ’,\$ ,(\#4) ,.PRODUCT . ,\#2);\#35= IFCRELASSIGNSTOGROUP (\$,\$,’M3 ’,\$ ,(\#5) ,.PRODUCT . ,\#2);\#36= IFCRELASSIGNSTOGROUP (\$,\$,’M4 ’,\$ ,(\#6) ,.PRODUCT . ,\#2);\#37= IFCRELSERVICESBUILDINGS (\$,\$,’Highway A9 ITS -enabled section

’,\$,\#2 ,(\#1));...

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Figure 8. Visualization of the BIM model of the ITS simulation scenario.

5. Summary and Conclusions

In this study, an IFC schema extension has been introduced to describe intelligenttransportation systems for roads, in an attempt to provide a formal basis facilitating BIM-based ITS simulations. A semantic model, which formally describes ITS for roads, hasbeen proposed to provide a technology-independent description on a meta level. With thesemantic model, constructed upon an analysis of knowledge sources relevant to semanticmodeling of ITS, a new concept for integrating ITS for roads into BIM data models has beenmaterialized as an IFC schema extension, which have not been addressed prior to this workfor intelligent transportation systems. For validating and verifying BIM-based simulationsof ITS for roads, a benchmark scenario of vehicular cloud formation has been modeledusing the IFC schema extension. The test software of the official IFC certification programhas been used for verification purposes, i.e., for checking the IFC schema extension and theexample IFC model representing the vehicular cloud formation scenario against syntacticaland semantic criteria. The results have shown that the proposed IFC schema extensiongrants proper semantic description of ITS components, relationships between ITS compo-nents, and ITS applications. Therefore, it can be concluded that the IFC schema extensionrepresents a sound formal basis to be used for BIM-based simulations of ITS for roads, notonly in research projects, but also in the BIM industry, where infrastructure constructionprocesses are yet to be (fully) digitalized. In future work, geometrical representation maybe included in the IFC schema extension proposed herein, which may be tested using realdata from field tests. Furthermore, the IFC schema extension may be enhanced by inte-grating and modeling further ITS use cases, focusing on ITS communication networks anddecentralized data-processing issues. Furthermore, BIM-based simulations that considerthe impact of ITS for roads on the environment are aspects that may be addressed in futureresearch endeavors.

Author Contributions: Conceptualization, K.S.; methodology, M.M. and K.S.; software, M.M.; val-idation, M.M.; formal analysis, M.M.; investigation, M.M.; resources, K.S.; data curation, M.M.;writing—original draft preparation, M.M.; writing—review and editing, K.S.; visualization, M.M.;supervision, K.S.; project administration, K.S.; funding acquisition, K.S. All authors have read andagreed to the published version of the manuscript.

Funding: This research is partially supported by the European Union through the European SocialFunds (ESF) and by the Thuringian Ministry for Economic Affairs, Science and Digital Society(TMWWDG) under grant 2017FGR0068.

Institutional Review Board Statement: Not applicable.

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Informed Consent Statement: Not applicable.

Data Availability Statement: The data presented in this study are available upon request from thecorresponding author. The data are not publicly available due to privacy restrictions on ongoingresearch.

Acknowledgments: The authors gratefully acknowledge the generous support provided by Theilerand Tauscher of Apstex GbR in verifying the IFC schema extension.

Conflicts of Interest: The authors declare no conflict of interest. The funders had no role in designingthe study; in collecting, analyzing, and interpreting the data; in writing the manuscript, or in decidingto publish the results. Any opinions, findings, conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the view of the sponsors.

AbbreviationsThe following abbreviations are used in this manuscript:

AEC Architecture, engineering, and constructionAVC Autonomous vehicular cloudsBIM Building information modelingbSI buildingSMART InternationalC-ITS Cooperative ITSETSI European Telecommunications Standards InstituteICN Information-centric networkingIFC Industry Foundation ClassesITS Intelligent transportation systemISO International Organization for StandardizationI2I Infrastructure-to-infrastructureLiDAR Light detection and rangingMEMS Micro-electro-mechanical systemsRFID Radio-frequency identificationVCC Vehicular cloud computingVCPS Vehicular cyber-physical systemsV2I Vehicle-to-infrastructureV2V Vehicle-to-vehicleV2X Vehicle-to-anything

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